Delivery model · assurance · support

A delivery path that leaves evidence behind

The approach connects business outcomes to architecture decisions, accepted increments and an operable service. Every phase has a decision to make, evidence to inspect and an owner for what happens next.

Enterprise delivery becomes fragile when discovery produces a document that engineering does not use, testing begins after the architecture has hardened, or operational ownership is deferred until launch. Wavelink keeps those concerns in one evidence path. The same user journeys and failure consequences used to frame the work inform the architecture, test strategy, telemetry, release plan and service objectives.

The method is intentionally adaptable. A focused integration, a multi-quarter platform replacement and a production support transition require different commercial and technical shapes. They still benefit from explicit boundaries, short feedback cycles, controlled environments and decision records. The engagement model sets the rhythm; the assurance expectations follow the risk of the system.

No service-level percentage, recovery target or compliance label is assumed to apply to every workload. Numeric commitments are confirmed only after the parties validate service hours, dependencies, workload behaviour, hosting boundaries, data obligations and support authority.

Engagement models

Choose the smallest structure that can own the outcome

The model determines decision cadence, client participation and the boundary of responsibility. It can change at an explicit gate when evidence shows that the work has a different shape.

Discovery and architecture

Best when the operational problem is understood but the system boundary, data path, migration risk or investment sequence is not.

StructureTime-bounded mapping, technical investigation and a thin proof around the highest-risk assumption. The output is a decision package rather than a feature promise.

Client roleProvide product, operational, security and data owners who can explain real cases and resolve policy questions.

Decision gateProceed, narrow, sequence differently or stop based on the architecture, evidence and cost range.

Outcome-led delivery

Best for a defined capability that can be accepted through working journeys, data reconciliation and operational evidence.

StructureIncremental delivery against prioritised outcomes. Scope is managed through acceptance criteria, dependency decisions and a visible risk register.

Client roleOwn priorities, policy decisions, access to dependent teams and acceptance of completed increments.

Decision gateRelease or revise each increment after functional, security, migration and operational checks appropriate to its risk.

Embedded engineering capability

Best when a client team owns a product or platform and needs additional engineering depth inside its existing roadmap and controls.

StructureEngineers join shared planning, code review, delivery and incident routines with a defined technical mission and exit criteria.

Client roleRetain product authority, repository and environment ownership, and integrate Wavelink contributors into the same quality system.

Decision gateReview capability transfer, delivery evidence and remaining dependency on the embedded team at agreed intervals.

Managed service transition

Best for an existing production service that needs clearer Tier 2 ownership, release assurance, incident coordination and reliability improvement.

StructureA measured transition establishes inventory, health indicators, access, runbooks, known failure modes and escalation boundaries before support acceptance.

Client roleRetain product decisions and Tier 1 user ownership while providing supplier authority, environment access and escalation contacts.

Decision gateAccept the support baseline only when the service can be observed, changed and recovered within the agreed boundary.

Delivery methodology

Reduce risk in inspectable phases

Phases may overlap, but their decisions remain distinct. The team should know whether it is defining the problem, proving a risk, scaling a known pattern or transferring production ownership.

01 · Frame
02 · Prove
03 · Build
04 · Transition
05 · Operate

01 · Frame

Establish the outcome, actors, records, dependencies, constraints and consequences of failure.

Trace representative journeys, exceptions and reconciliation paths

Map data authority, access, residency and retention questions

Record assumptions, external dependencies and acceptance evidence

Phase evidenceSystem boundary, outcome measures, risk register, decision owners and a sequenced first slice.

02 · Prove

Exercise the assumption most likely to invalidate the design before broad implementation begins.

Build a thin vertical path across the real integration and data boundaries

Measure workload, latency, failure and recovery behaviour where relevant

Record architecture decisions and alternatives with observed evidence

Phase evidenceWorking proof, updated architecture, interface contracts, test strategy and a proceed-or-revise decision.

03 · Build

Deliver production-shaped increments that include security, telemetry and documentation.

Implement prioritised journeys with automated rule and contract checks

Use backward-compatible data change and controlled artefact promotion

Review demonstrations against acceptance evidence, not presentation alone

Phase evidenceAccepted increments, versioned source and artefacts, automated checks, dashboards and release records.

04 · Transition

Move data, users and operational authority without obscuring unresolved risk.

Rehearse migration, cutover, rollback, restoration and provider escalation

Train administrators and operators through real procedures

Document known limitations, owners and post-launch observation windows

Phase evidenceReconciliation reports, accepted runbooks, access matrix, recovery evidence and signed ownership boundaries.

05 · Operate

Use production evidence to protect reliability and direct the next improvement.

Review user-visible service indicators, incidents, capacity and change failure

Remove recurring manual work and address repeated failure conditions

Rehearse recovery and update documentation as the system changes

Phase evidenceService reviews, incident actions, reliability backlog, capacity decisions and current recovery records.

Environments & data

Promotion is controlled; environments have distinct purposes

A separate environment is useful only when its ownership, data rules, change path and expected fidelity are understood.

Developer and component

Fast feedback on domain rules, component behaviour and local integration contracts without depending on shared infrastructure.

Versioned local configuration and repeatable dependencies

Synthetic or deliberately minimised test data

Unit, component, static-analysis and secret-detection checks

Integration

Exercise service contracts, asynchronous flows, schema changes and failure handling across deployable boundaries.

Isolated credentials and non-production trust boundaries

Contract fixtures plus provider simulators where access is limited

Replay, retry, idempotency and reconciliation scenarios

Acceptance

Allow product, operational and security owners to inspect production-shaped journeys before release.

Release-candidate artefacts promoted from the same build path

Masked, synthetic or specifically approved data handling

Acceptance, accessibility, migration and operational-readiness evidence

Production

Run the accepted service under least privilege, measured objectives and explicit change authority.

Restricted access with auditable emergency procedure

Observable deployment, health, dependency and user-journey signals

Verified backup, restoration, rollback and incident communication paths

Testing & release practice

Test the property at the layer that owns it

A large end-to-end suite cannot compensate for ambiguous business rules or untested recovery. Assurance combines focused automated checks with production-shaped exercises.

Domain and component assurance

Business invariants, permissions and deterministic transformations are tested close to the code that owns them. Reviews focus on boundary conditions and the consequence of an incorrect decision.

Unit and property-oriented tests for critical rules

Static analysis, dependency review and code review

Traceability from acceptance scenario to protected behaviour

Contract and data assurance

Interfaces are tested as contracts with explicit versions, error behaviour and compatibility expectations. Data movement is assessed through counts, control totals, checksums or business reconciliation appropriate to the record.

Consumer/provider contract checks

Schema compatibility and migration rehearsal

Duplicate, ordering, partial-failure and replay scenarios

Journey and non-functional assurance

A focused set of user journeys verifies the assembled service. Load, accessibility, security and resilience checks follow the workload and risk rather than a generic checklist.

Critical-path browser or API journeys

Workload model with latency, saturation and queue observations

Threat-led security checks and controlled failure exercises

Release and recovery assurance

An artefact is built once and promoted through controlled environments. Database changes preserve compatibility across the rollout window, and health signals determine whether a release proceeds, pauses or rolls back.

Versioned artefact, approvals and deployment record

Progressive release or maintenance plan appropriate to the system

Rollback, restoration and post-release verification evidence

Security & compliance posture

Controls follow threats, data and responsibility

The delivery does not rely on an unsupported certification claim. It maps applicable client obligations and system threats to controls that can be evidenced and operated.

Control posture

Security begins during framing with data classification, actors, trust boundaries, abuse cases and supplier dependencies. The team identifies which decisions require segregation of duties, which records require stronger integrity evidence, and where credentials or personal information may cross a boundary. The client remains the authority for legal interpretation and risk acceptance.

Implementation uses least privilege, managed secrets, reviewed dependencies, protected build paths and auditable administrative actions. Cryptographic choices are recorded with their purpose and lifecycle so algorithms, certificates and keys can change without an uncontrolled rewrite. Vulnerability findings are prioritised by exploitability and system consequence rather than a score alone.

Before transition, security-relevant monitoring, incident roles, access review and recovery procedures are exercised with the receiving operators. Where a client requires alignment to a law, policy or standard, the engagement creates a control-and-evidence matrix for the agreed scope; it does not imply organisation-wide certification.

Delivery checks

Threat model and data-flow review at architecture boundaries

Identity, privilege and segregation-of-duties checks

Secrets, dependency and software-supply controls in delivery pipelines

Logging and alerting for security-relevant actions and failures

Cryptographic inventory, key ownership and migration considerations

Incident, restoration and access-revocation rehearsal before handover

SLAs & support tiers

Production support with explicit ownership boundaries

A support model is effective when the first observer, technical resolver, product decision-maker and external provider know when and how work passes between them.

Tier labels describe responsibilities, not prestige. The client or its service desk commonly owns user communication and initial triage. Wavelink’s managed-services scope is positioned at Tier 2: application, integration, data or platform diagnosis and restoration within the accepted service boundary. A cloud, telecommunications, software or other external provider remains Tier 3 for the services it controls.

The final assignment may differ where Wavelink operates a broader service, but the ownership matrix is agreed before support acceptance. Product decisions, legal notifications, commercial provider authority and changes outside the managed boundary remain with named client owners unless a contract states otherwise.

Tier 1 · User and request intake

OwnerClient service desk or designated operational team

Confirm affected users, capture time and evidence, resolve known user issues, communicate status and identify the supported service.

HandoffEscalate with impact, reproduction evidence, timestamps, identifiers and actions already attempted.

Tier 2 · Technical diagnosis and restoration

OwnerWavelink within the agreed managed-service scope

Correlate telemetry, diagnose application or platform behaviour, apply approved mitigation, coordinate release or recovery and maintain the technical incident record.

HandoffReturn user communication to Tier 1; request product authority from the client; escalate provider-controlled faults with technical evidence.

Tier 3 · Product or infrastructure provider

OwnerRelevant external provider or specialist product team

Resolve defects, capacity or service failures inside a provider-controlled product, network, cloud service or licensed platform.

HandoffWavelink coordinates technical evidence where authorised; the client retains commercial and contractual provider authority unless delegated.

Service objectives are measured at the user-visible boundary

Availability is defined for a named journey during stated service hours and with clear treatment of degraded operation and external dependencies. A healthy server is not enough if a user cannot complete the transaction. Measurement sources, sampling, exclusions and reporting intervals are agreed with the objective.

Incident objectives separate acknowledgement, diagnosis, mitigation and restoration. Severity is based on impact, scope, urgency and available workaround. Recovery objectives state acceptable data loss and restoration time for the records and workflows in scope; backup retention is not presented as proof that restoration will succeed.

Reliability reviews connect incidents, near misses, change failure, capacity and recurring manual work. Where error budgets are appropriate, they provide a decision rule for balancing change with stability. Any contractual numbers are inserted only after discovery and operational validation.

Availability boundaryNamed user journey, service hours and dependency treatment

Incident objectiveImpact-based acknowledgement, mitigation and restoration stages

Recovery objectiveValidated data-loss and restoration requirements per workload

Service reviewReliability evidence, incident actions, capacity and change risk